ALLU DIWAKAR
21BCE9213
diwakar.21bce9213@vitapstudent.ac.in
1. Upload the dataset to MySQL and integrate with Tableau, delete the unnecessary columns,
explore and visualize the dataset using Tableau.
• Title:
Exploratory Data Analysis and Visualization of Supermarket Sales Data with MySQL and
Tableau.
• Abstract:
This project involves the integration of a historical sales dataset from a supermarket into
MySQL and the subsequent exploration and visualization of the data using Tableau. The
dataset contains various attributes related to sales transactions, such as branch information,
customer type, product categories, prices, and more. Unnecessary columns will be removed
to streamline the dataset. Through Tableau, we will create insightful visualizations to gain a
comprehensive understanding of the sales trends and customer behaviour within the
supermarket.
• Materials and methods:
- Dataset Selection: A historical sales dataset from a supermarket is chosen for analysis.
- MySQL Integration: The dataset is uploaded and integrated into a MySQL database.
- Column Selection: Unnecessary columns are identified and removed to optimize the dataset.
- Tableau Integration: MySQL is connected to Tableau for data visualization.
- Data Exploration: Exploratory data analysis techniques are applied to understand the
dataset.
- Visualization: Various visualizations are created using Tableau to gain insights into sales
trends and customer behaviour.
I B M C o g n o s A n a l y t i c s
A s s i g n m e n t - 0 3
Allu Diwakar – 21BCE9213
• Introduction:
With the rapid growth of supermarkets in densely populated cities, understanding sales trends
and customer behaviour is crucial for staying competitive. This project aims to leverage
MySQL and Tableau to streamline the analysis of a historical sales dataset. By integrating
the data, removing unnecessary columns, and creating insightful visualizations, we seek to
uncover valuable insights that can inform decision-making and improve overall business
strategies.
• Implementation:
➢ MySQL Integration:
1.open MySQL Workbench:
Allu Diwakar – 21BCE9213
2.create a schema:
3. Import the data from local data set:
Allu Diwakar – 21BCE9213
Allu Diwakar – 21BCE9213
Allu Diwakar – 21BCE9213
4. preprocess the data using SQL commands:
Allu Diwakar – 21BCE9213
Allu Diwakar – 21BCE9213
➢ Tableau Integration:
1.Open Tableau Desktop
Allu Diwakar – 21BCE9213
2. select MySQL in Connect to a Server option
Allu Diwakar – 21BCE9213
➢ Data Exploration and Visualization:
1. Which product categories are the most popular among customers and Which product categories generate
the highest revenue?
Allu Diwakar – 21BCE9213
2. What are the sales trends over time, and are there any notable patterns or spikes?
Allu Diwakar – 21BCE9213
3. How do sales vary by city and branch?
4. Compare how member and non-member customers contribute to total sales, broken down by gender.
Allu Diwakar – 21BCE9213
Profit Analysis and Insights in Supermarket Sales Data: A Visual Exploration
Calculate Profit:
Create a calculated field named "Profit" by subtracting COGS from Total Sales. i.e., Profit = Total - COGS
Calculate Profit Margin:
Create a calculated field named "Profit Margin" by dividing Profit by Total Sales (Total = Gross income + Tax)
i.e., Profit Margin = Profit / Total Sales
Allu Diwakar – 21BCE9213
Allu Diwakar – 21BCE9213
Profit Trend Over Time: To Analyze how profit varies over time and identify trends.
Profit by Product Line: To Determine which product lines are most profitable.
Allu Diwakar – 21BCE9213
Profit Margin by Payment Method: To Understand how profit margin varies by payment method.
Profit vs. Quantity: To Explore the relationship between the quantity of products sold and profit.
Allu Diwakar – 21BCE9213
Profit Margin Distribution: To understand the distribution of profit margins across different product lines.
• Results.
The project results in a streamlined dataset optimized for analysis. Through Tableau
visualizations, we gain insights into sales trends across branches, customer segmentation,
popular product categories, and more. These insights can inform strategic decisions,
marketing efforts, and inventory management to enhance the supermarket's competitive edge
in the market.
• References:
https://help.tableau.com/current/pro/desktop/en-us/buildexamples_scatter.htm
Allu Diwakar – 21BCE9213
